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在机载相控阵雷达下视情况下，多普勒展宽的时变杂波可以用自适应时空二维处理器得到最优的抑制。然而对于大型阵列的实时应用来说，这种最优时空二维处理却很难实现，这是由于它要求很高的计算量（以典型的采样协方差矩阵求逆算法￣［２］为例，其运算量大约为每次迭代Ｏ｛（ＮＭ）￣２｝，其中Ｎ为阵元数，Ｍ为时间采样数）。在本文中，首先通过杂波子空间分析证明了杂波自由度小于Ｎ＋Ｍ，而且阵列信号在经过多普勒滤波后，单个多普勒滤波器输出的杂波自由度很小，从而可以用一个仅有Ｎ＋Ｍ个自由度的低阶（部分自适应）处理器来实现准最优的杂波抑制；随后，提出了用Ｎ＋Ｍ个多普勒─特征波束（多普勒滤波器后跟空间特征波束）来近似杂波子空间的办法，并据此方法构造了一个使用这种多普勒一特征波束的广义旁瓣对消器并用它实现了准最优的杂波抑制，所需计算量仅为每次迭代Ｏ｛Ｎ＋Ｍ）Ｎ＋（Ｎ＋Ｍ）￣２｝。由于空间特征波束所具有的误差补偿能力，该处理器在实际应用中对于处理器自由度不足是不敏感的。
Under the condition of airborne phased array radar, Doppler broadening time-dependent clutter can be optimally suppressed by adaptive spatio-temporal two-dimensional processor. However, this optimal spatio-temporal 2D processing is difficult to achieve for real-time applications of large arrays due to the high computational requirements (using a typical sampling covariance matrix inversion algorithm [2] as an example) , The computational complexity is about O {(NM) ~ 2} for each iteration, where N is the number of elements and M is the number of time samples. In this paper, we first prove that clutter’s degree of freedom is less than N + M by clutter subspace analysis, and the Doppler output of the array signal is very small after the Doppler filtering, so that only one Then a N + M Doppler-eigenbeam (Doppler filter followed by a spatial eigenbeam) is proposed to achieve the quasi-optimal clutter suppression with N + M DOF lower-order (partially adaptive) A method of approximating clutter subspace is proposed and a generalized sidelobe canceller using this Doppler-eigenbeam is constructed according to the method. Quasi-optimal clutter suppression is achieved by using this method. Iteration O {N + M) N + (N + M) ~ 2}. Due to the error compensation capability of the spatial eigenbeam, this processor is not sensitive to the lack of processor’s freedom in practical applications.